Search: “evaluation”

Uncertainty Quantification in Machine Learning for Biosignal Applications -- A Review

arXiv:2312.09454v3 Announce Type: replace-cross Abstract: Purpose: Uncertainty Quantification (UQ) has gained traction in an attempt to improve the interpretability and robustness of machine learning

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Unfold The World: Factorize 4D Properties in Reinforcing Spatial Reasoning

DGX agent

arXiv:2609.03729v1 Announce Type: new Abstract: Despite the remarkable prowess of Vision-Language Models (VLMs) in general multimodal tasks, they remain fundamentally ``flat'' when reasoning about the

safetyarxiv-cs-cv

4 Sept 2026

Virtual Testing of Automated Driving Systems through Credible Simulations

arXiv:2609.03760v1 Announce Type: new Abstract: Simulation is increasingly used to support safety-related decision-making in road transport, particularly for the assessment and approval of automated d

safetyarxiv-cs-ro

Local Ai

WeatherNext 3: Increasing resolution and performance of global weather models with raw observations

arXiv:2609.03582v1 Announce Type: new Abstract: State-of-the-art AI weather models have shown impressive medium-range forecast skill and computational efficiency, but suffer two key shortcomings: thei

local-aiarxiv-cs-lg

What Else Needs Fixing? Exploring Cost-Effective Test-Time Compute for Revision Propagation in Artifacts Generated Through Conversation

model-releasesarxiv-cs-cl

arXiv:2609.03254v1 Announce Type: new Abstract: Large Language Models (LLMs) often help users generate artifacts through iterative cycles of generation and revision in conversation. A challenge here i

What Matters for Aggressive Decoding-Time KV Eviction? Temporal Aggregation and Ranking Preservation

arXiv:2609.03515v1 Announce Type: new Abstract: Decoding-time KV cache compression research focuses heavily on designing better token scoring functions, while the temporal rule that aggregates scores

WIDE: Wildcard Inference with Dynamic Expansion for Cross-Modal Generative Retrieval

arXiv:2609.03554v1 Announce Type: cross Abstract: Generative retrieval has demonstrated significant success by unifying representation learning and search into a single sequence-to-sequence generation

WorldReward: Reward Modeling for Camera-Conditioned World Models

arXiv:2609.03952v1 Announce Type: new Abstract: Camera-conditioned world models generate interactive videos in which commanded actions should induce the expected scene changes while appearance, geomet

A Common Measure of Communication for Speech Brain-Computer Interfaces

arXiv:2609.02887v1 Announce Type: new Abstract: Speech brain-computer interfaces (speech BCIs) translate neural activity into language, offering a path towards restoring speech for people with paralys

A Layered Taxonomy for Chinese Learner Grammatical Error Annotation

arXiv:2609.02153v1 Announce Type: new Abstract: Grammatical error annotation in Chinese learner writing requires labels that are both consistent and linguistically meaningful. This paper proposes a la

researcharxiv-cs-cl

Applications

A Unified Particle Filter LSTM for Data-Driven Process Simulation

arXiv:2609.01967v1 Announce Type: new Abstract: Data-driven process simulation aims to generate realistic case trajectories from historical event logs without requiring an explicitly specified model o

applicationsarxiv-cs-lg

A Unified Rate-Distortion Perspective on Vector, Product, and Scalar Quantization

arXiv:2609.02107v1 Announce Type: cross Abstract: Discrete visual tokenization, predominantly driven by vector, scalar, and product quantization, lacks a unified conceptual framework for understanding

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Tutorials

Achieving More with Less: A Tensor-Optimization-Powered Ensemble Method

arXiv:2408.02936v3 Announce Type: replace Abstract: Ensemble learning is a method that leverages weak learners to produce a strong learner. However, obtaining a large number of base learners requires

tutorialsarxiv-cs-lg

Agents

Achieving Olympiad-Level Geometry Large Language Model Agent via Complexity Boosting Reinforcement Learning

arXiv:2512.10534v4 Announce Type: replace Abstract: Large language model (LLM) agents exhibit strong mathematical problem-solving abilities and can even solve International Mathematical Olympiad (IMO)

agentsarxiv-cs-ai

Action abstractions for amortized sampling

arXiv:2410.15184v2 Announce Type: replace-cross Abstract: As trajectories sampled by policies used by reinforcement learning (RL) and generative flow networks (GFlowNets) grow longer, credit assignmen

Actor as Its Own Critic: Unifying Region Understanding and Localization via CycleGRPO

arXiv:2607.11581v2 Announce Type: replace Abstract: This paper introduces Actor as Its Own Critic, a unified reinforcement learning framework, Cycle Group Relative Policy Optimization (CycleGRPO), tha

AdaMem: Learning What to Remember with Adaptive Memory Policies for Personalized Agents

arXiv:2606.21144v2 Announce Type: replace-cross Abstract: Long-term memory systems allow LLM agents to preserve information beyond a single context window, but most systems focus on storing and retrie

Adversarial Stress Testing of Outlier Detection in Subjective Image Quality Assessment

arXiv:2509.06554v2 Announce Type: replace-cross Abstract: In subjective image and video quality assessment, observers rate or compare selected stimuli. Before calculating mean opinion scores (MOSs), u

AffectDelta: Beyond Emotion Labels for Image Editing

arXiv:2609.02616v1 Announce Type: new Abstract: Emotion-driven image editing aims to evoke a specified target emotion by modifying emotion-relevant visual cues in a source image, while preserving the

safetyarxiv-cs-cv

Agent Memory Is a Surface for Endogenous Authorization Laundering

arXiv:2609.01836v1 Announce Type: cross Abstract: Long-running LLM agents rely on persistent memory to carry state across interactions, including permissions, restrictions, and revocations. When memor

AI Contextual Measurement for Recovering Individual and Group-Level Effects: Validation Against Survey Measures and an Occupational Application

arXiv:2609.02821v1 Announce Type: new Abstract: Researchers increasingly use artificial intelligence to construct measures of social, organizational, and occupational characteristics that are absent f

Allocate Before You Embed: Adaptive Visual Input Allocation for Video Embeddings

arXiv:2609.01778v1 Announce Type: new Abstract: Large-scale video retrieval requires embedding models to encode long and diverse videos under tight visual-input and inference budgets. Existing methods

Are Non-English Papers Reviewed Fairly? Language-of-Study Bias in NLP Peer Reviews

arXiv:2604.07119v2 Announce Type: replace Abstract: Peer review plays a central role in the NLP publication process, but is susceptible to various biases. Here, we study language-of-study (LoS) bias:

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Asymmetric Paired-Annotation Learning for Multi-Structure ULF Pediatric Brain MRI Segmentation

arXiv:2609.02210v1 Announce Type: new Abstract: Portable ultra-low-field (ULF) MRI can expand access to pediatric neuroimaging, but segmentation at 0.064 T remains challenging because anatomical bound

researcharxiv-cs-cv

Before the Script, Set the Stage: How Worldview Simulation Amplifies Psychologically Grounded Persuasion in Multi-Turn Jailbreaking

arXiv:2609.02414v1 Announce Type: cross Abstract: Multi-turn jailbreak attacks demonstrate that harmful intent can be distributed across dialogue, yet existing methods obscure what conversational mech

Breaking the Geometric Bottleneck: Contrastive Expansion in Asymmetric Cross-Modal Distillation

arXiv:2603.06698v3 Announce Type: replace Abstract: Knowledge distillation between asymmetric architectures often induces severe geometric constraints on the learned representation space. We investiga

CA-OPD: Confidence-Aware On-Policy Distillation for Structured Visual Prediction

arXiv:2609.02401v1 Announce Type: new Abstract: Autoregressive vision language models unify heterogeneous perception tasks but are highly susceptible to compounding errors. On-policy distillation (OPD

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CACTUS: Mask-Guided Semantic Clean-Label Backdoors in Decentralized Federated Learning

arXiv:2609.02450v1 Announce Type: new Abstract: Semantic triggers in federated learning (FL) can be less conspicuous than synthetic patches, but sample-dependent placement may weaken backdoor implanta

CAPTURE: Disentangling Preference Drift from Memory Poisoning in Personalized LLM Agents

model-releasesarxiv-cs-lg

arXiv:2609.02265v1 Announce Type: new Abstract: Personalized language agents use persistent memory to adapt to users over time, but the same mechanism creates an attack surface. When new information c

CAT-Flow: Curvature-Adaptive sTeps for Flow Matching

arXiv:2609.01746v1 Announce Type: new Abstract: Flow Matching has emerged as a leading framework for generative modeling, powering state-of-the-art systems such as FLUX and Stable Diffusion 3.5. Howev

CHisAgent: A Multi-Agent Framework for Event Taxonomy Construction in Ancient Chinese Cultural Systems

arXiv:2601.05520v2 Announce Type: replace Abstract: Despite strong performance on many tasks, large language models (LLMs) show limited ability in historical and cultural reasoning, particularly in no

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Cliff: Learning Process Rewards from the First Mistake

arXiv:2609.02817v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) has emerged as a powerful paradigm for large language model (LLM) post-training, but its reliance

safetyarxiv-cs-lg

CliffRank: A Dual-Branch Framework for Activity-Cliff Ranking Prediction

arXiv:2609.01673v1 Announce Type: cross Abstract: Activity-cliff ranking remains difficult because local structural changes can cause large activity differences, while high-quality data that resolve t

CoMerge: Conflict-Driven Preference Optimization for Multi-Task Model Merging

arXiv:2609.02273v1 Announce Type: new Abstract: Model merging provides an efficient paradigm for constructing multi-task large language models (LLMs) without full model retraining, yet it remains chal

Competitive Market Behavior of LLMs

arXiv:2609.02580v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed as economic agents, yet there is little evidence whether LLM agents are suited for participatin

Data-Efficient Networks for Multi-Contrast MRI Reconstruction based on a Generalized Content/Style Prior

arXiv:2609.01959v1 Announce Type: cross Abstract: Multi-contrast MR scans contain redundant structural information that can be leveraged during reconstruction and potentially accelerate acquisition ti

Dictionary-Guided Mutation Operators for Automated HDL Repair

arXiv:2609.01775v1 Announce Type: cross Abstract: Automated repair of Hardware Description Language (HDL) designs remains challenging due to the large search space of candidate repairs and the strict

DiDrive: A Risk-Aware Hierarchical Diffusion Framework for Safe Offline Reinforcement Learning in Autonomous Driving

model-releasesarxiv-cs-lg

arXiv:2609.01609v1 Announce Type: new Abstract: While diffusion models effectively capture multimodal behavioral priors for autonomous driving, offline reinforcement learning (RL) policies remain susc

Tutorials

Differentiable Electricity-Market Clearing for Gradient-Based Planning

arXiv:2609.02646v1 Announce Type: new Abstract: Planning a large data center is difficult because a facility big enough to matter changes the electricity prices it will pay. Those prices are set by ma

tutorialsarxiv-cs-lg

DiffIE: Diffusion-based Open Information Extraction

arXiv:2609.02315v1 Announce Type: cross Abstract: A single sentence often expresses multiple valid relational triplets, which makes Open Information Extraction (OpenIE) fundamentally a multi-output ta

Diversifying Long Prompt Image Generation through Structured Prompt Embedding Space Sampling

arXiv:2511.20251v2 Announce Type: replace Abstract: Modern text-to-image models produce impressive visual results from richly specified prompts, yet their behavior under long prompts remains insuffici

Tutorials

Do Tabular Foundation Models Know Physics? Contamination, Units, and the Deterministic Limit

arXiv:2609.02766v1 Announce Type: new Abstract: Tabular foundation models (TFMs) learn to fill in tables the way language models fill in text, and tables are arguably the format in which most physical

tutorialsarxiv-cs-lg

Applications

Door-in-the-Face Requests and Refusal Behaviour in Large Language Models

arXiv:2609.02707v1 Announce Type: new Abstract: Does the door-in-the-face technique work on language models? In humans, a large request that is refused makes a smaller follow-up request more likely to

applicationsarxiv-cs-ai

Applications

Doppio: A Dataset for Contactless Weight Estimation of Falling Particles

arXiv:2609.02528v1 Announce Type: new Abstract: Measuring the mass of powder, including falling particles, is a common task in industrial applications. While scales are effective for static measuremen

applicationsarxiv-cs-cv

Double-Bounded Nonlinear Optimal Transport for Size Constrained Min Cut Clusterin

model-releasesarxiv-cs-lg

arXiv:2501.18143v2 Announce Type: replace Abstract: Min cut is an important graph partitioning method. However, current solutions to the min cut problem suffer from slow speeds, difficulty in solving,

Efficient GUI Agents: A Systems Survey of Observation, Memory, Action, and Runtime Optimization

model-releasesarxiv-cs-cl

arXiv:2609.02309v1 Announce Type: new Abstract: GUI agents increasingly operate across websites, mobile apps, and desktop environments, yet the field still reports progress primarily through task succ

Efficient Passive Acoustic Monitoring of Killer Whales Using a Two-Stage Detection and Ecotype Classification Cascade

arXiv:2609.01792v1 Announce Type: cross Abstract: Passive acoustic monitoring of killer whales is particularly important for conservation of the endangered Southern Resident killer whale population, b

Eliciting ESG Preferences for Reinforcement Learning-Based Portfolio Optimization

arXiv:2609.02677v1 Announce Type: cross Abstract: Modern portfolio management increasingly demands a balance between traditional risk-adjusted returns and strict Environmental, Social, and Governance

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